Computer scientists' definition of texture and style can be traced to the research of Bela Julesz on texture discrimination in humans [1]}, [2]}, [3]}. Julesz used a computer to generate a grid of 'micropatterns' (i.e. image patches) using a random Markov process (i.e. micropatterns were either sampled independently or depended only on their immediately neighbors). Different distributions of micropatterns were used for different sections of the grid, for example the right and left halves of the image might use different distributions of micropatterns, or the central portion of the image might use a different distribution than the boundary. Julesz found that human perception was extremely sensitive to the first and second order statistics of micropatterns (e.g. average brightness, variance of dot deviation from uniform grid, rotations other than 180\(^\circ \) ), but careful scrutiny was required to differentiate between textures of micropatterns that differed only in higher order statistics (e.g. mirror images, words vs random letter sequences, one vs two small white holes in black circles). Later work by Julesz discovered that some higher level statistics (whether small dots were inside or outside a hollow black ring) were easily detected, however the core idea remained that texture was a local phenomena which could be captured by summary statistics of micropatterns (i.e. image patches). Quoting [4]}, this lead to a high-level framework for texture synthesis: "(1) picking the right set of statistics to match, (2) finding an algorithm that matches them."
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